Clustering of marine-debris- and \emph{Sargassum}-like drifters explained by inertial particle dynamics}

TL;DR

This study uses inertial particle dynamics theory to explain the clustering behavior of marine debris and Sargassum-like drifters, improving trajectory simulations by accounting for physical properties.

Contribution

It applies a recent Maxey-Riley inertial particle theory to real ocean data, enhancing the modeling of floating object movements at the surface.

Findings

Inertial modeling improves trajectory accuracy over fluid-following models.

Debris-like drifters' simulated trajectories closely match observed data.

Sargassum-like drifters show larger deviations, indicating additional physical factors are relevant.

Abstract

Drifters designed to mimic floating marine debris and small patches of pelagic \emph{Sargassum} were satellite tracked in four regions across the North Atlantic. Though subjected to the same initial conditions at each site, the tracks of different drifters quickly diverged after deployment. We explain the clustering of drifter types using a recent Maxey-Riley theory for surface ocean inertial particle dynamics applied on multidata-based mesoscale ocean currents and winds from reanalysis. Simulated trajectories of objects at the air-sea interface are significantly improved when represented as inertial (accounting for buoyancy and size), rather than as perfectly Lagrangian (fluid following) particles. Separation distances between simulated and observed trajectories were substantially smaller for debris-like drifters than for \emph{Sargassum}-like drifters, suggesting that additional consideration of its physical properties relative to fluid velocities may be useful. Our findings can be applied to model variability in movements and distribution of diverse objects floating at the ocean surface.